metadata
library_name: transformers
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: wav2vec2-gpt2-enc-dec
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: cs
split: train[:500]
args: cs
metrics:
- name: Wer
type: wer
value: 0.8489326765188834
wav2vec2-gpt2-enc-dec
This model is a fine-tuned version of on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3276
- Wer: 0.8489
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.08
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.9498 | 1.5625 | 50 | 0.6548 | 0.9324 |
| 0.4531 | 3.125 | 100 | 0.3959 | 0.9020 |
| 0.4087 | 4.6875 | 150 | 0.3735 | 0.8894 |
| 0.3992 | 6.25 | 200 | 0.3572 | 0.8747 |
| 0.3725 | 7.8125 | 250 | 0.3500 | 0.8763 |
| 0.3635 | 9.375 | 300 | 0.3419 | 0.8626 |
| 0.3647 | 10.9375 | 350 | 0.3381 | 0.8632 |
| 0.36 | 12.5 | 400 | 0.3340 | 0.8566 |
| 0.3588 | 14.0625 | 450 | 0.3316 | 0.8547 |
| 0.362 | 15.625 | 500 | 0.3299 | 0.8547 |
| 0.3613 | 17.1875 | 550 | 0.3280 | 0.8498 |
| 0.3505 | 18.75 | 600 | 0.3276 | 0.8489 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0